6 papers
Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
Zhihua Hua, Junli Wang, Pengfei LI +6
Global navigation information and local scene understanding are two crucial components of autonomous driving systems. However, our experimental results indicate that many end-to-en…
Semore: VLM-guided Enhanced Semantic Motion Representations for Visual Reinforcement Learning
Wentao Wang, Chunyang Liu, Kehua Sheng +2
The growing exploration of Large Language Models (LLM) and Vision-Language Models (VLM) has opened avenues for enhancing the effectiveness of reinforcement learning (RL). However,…
UniSplat: Unified Spatio-Temporal Fusion via 3D Latent Scaffolds for Dynamic Driving Scene Reconstruction
Chen Shi, Shaoshuai Shi, Xiaoyang Lyu +4
Feed-forward 3D reconstruction for autonomous driving has advanced rapidly, yet existing methods struggle with the joint challenges of sparse, non-overlapping camera views and comp…
PriorFusion: Unified Integration of Priors for Robust Road Perception in Autonomous Driving
Xuewei Tang, Mengmeng Yang, Tuopu Wen +7
With the growing interest in autonomous driving, there is an increasing demand for accurate and reliable road perception technologies. In complex environments without high-definiti…
DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving
Chen Shi, Shaoshuai Shi, Kehua Sheng +2
Data-driven learning has advanced autonomous driving, yet task-specific models struggle with out-of-distribution scenarios due to their narrow optimization objectives and reliance…
An End-to-End Learning-Based Multi-Sensor Fusion for Autonomous Vehicle Localization
Changhong Lin, Jiarong Lin, Zhiqiang Sui +4
Multi-sensor fusion is essential for autonomous vehicle localization, as it is capable of integrating data from various sources for enhanced accuracy and reliability. The accuracy…